AI-enabled qualitative analysis of menstrual health

Answer: Researchers should embed WASH, privacy, disposal, and stigma probes in interview guides from the first question. The PLOS One study (24 July 2026) shows that structural themes (water scarcity, toilet privacy, waste disposal) and socio-cultural themes (shame, silence) consistently co-occur, so interviewers should capture both material and normative detail.

Supporting detail: PLOS One reports participants saying things like, "The toilet near our room has no door. Boys and men walk by all the time. I feel scared to change my clothes there" (IDI-04), which suggests an interviewer prompt on toilet design, lighting, and perceived safety is essential during data collection (PLOS One, 24 July 2026).

Answer: Programs should map qualitative codes to measurable WASH indicators such as private toilet access, continuous water supply, and safe disposal options. The PLOS One authors directly link inadequate WASH with risky practices and psychosocial harms in their 24 July 2026 paper.

Supporting detail: PLOS One documents actions like hidden disposal into drains and drying cloths under beds, which programs can convert into monitoring indicators (e.g., percent of households with lockable toilets, percent with disposal bins) and measure alongside qualitative narratives (PLOS One, 24 July 2026). For technical guidance on integrating MHH into WASH programs, see the UNICEF guidance on menstrual health and hygiene.

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

Practical fit: PLOS One required thematic coding across three cross-cutting domains (structural-environmental, socio-cultural stigma, gendered inequities); Evidence synthesis via Evidano can automate initial code suggestions, surface co-occurrence patterns, and produce frequency and cross-segment summaries to speed analytic consensus.

Problem statement: the PLOS One team restricted full transcripts for confidentiality (PLOS One, 24 July 2026).

Evidano feature: Evidano supports encrypted uploads and PII redaction during transcription, plus controlled access to de-identified excerpts for auditors, which helps teams reproduce coding while protecting participants.

Problem statement: PLOS One used a combined inductive and deductive approach and reconciled coder differences in consensus meetings (PLOS One, 24 July 2026).

Evidano feature: Evidano provides AI-assisted code suggestions anchored to seed codes, automated co-occurrence matrices, and visual hierarchical code→subcode maps, reducing the time spent on initial codebook building and inter-coder calibration. See Evidano features for specifics.

Problem statement: PLOS One includes many participant quotations but manual extraction is time consuming (PLOS One, 24 July 2026).

Evidano feature: Evidano indexes transcripts for rapid retrieval of verbatim quotes by code, demographic tag, or date and generates tables that show code frequency by subgroup (e.g., adolescents vs adults), so teams can produce policy briefs faster.

Problem statement: the PLOS One team recorded interviews in Bengali and used back-checked translations for rigor (PLOS One, 24 July 2026).

Evidano feature: Evidano provides transcription with custom dictionaries, bilingual translation workflows, and back-translation checks to preserve participant meaning while enabling English analysis. See Evidano speech-to-text.